Computers are being exploited increasingly to enable commerce between firms (e.g., businesses) and their clients. For example, many client transactions are performed via communication with one or more websites of a firm. In any event, since clients often are identified uniquely in computer-logged activities, client transactions with a firm can be stored as data for analysis. The activities of individual clients can be mined to provide information about client behavior.
Clients can engage in commerce with a firm in a contractual or non-contractual setting. In a contractual setting, the firm may provide goods/services under an agreement that is maintained and/or renewed explicitly or implicitly over time and that is terminated expressly. For example, the firm may provide cable television service to clients via a monthly contract that can be terminated by each client at the end of any month. As another example, the firm may be a bank that provides banking services to account holders that entrust the bank with their money and that remain clients as long as some of the money remains with the bank. Accordingly, commerce performed in a contractual setting allows a firm to observe when clients become permanently inactive, which is referred to as client “churning.” Thus, a firm in a contractual setting can identify its active client base with accuracy. In contrast, in a non-contractual setting, a firm may provide goods/services on demand, without any agreement about whether or not a client will remain active with the firm.
Distinguishing active clients from inactive ones in a non-contractual setting can be problematic. Clients that are still active, but have not exhibited recent activity, cannot be distinguished unambiguously from those that have churned. Thus, in a non-contractual setting, clients often are deemed as active or inactive based on an approach using an arbitrary measure of activity, such as whether or not a client has performed a transaction with the firm within a given period of time, such as within the past year. However, this approach is inaccurate and reactive, instead of proactive.